ArticleDisease markers2022
A Prognosis Marker Dynein Cytoplasmic 1 Heavy Chain 1 Correlates with EMT and Immune Signature in Liver Hepatocellular Carcinoma by Bioinformatics and Experimental Analysis.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
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- PRMT5-mediated arginine methylation of FXR1 is essential for RNA binding in cancer cells.Nucleic acids research · 2024Article
- Transcriptomic screening of novel targets of sericin in human hepatocellular carcinoma cells.Scientific reports · 2024Article
- Comprehensive analysis indicated that NDE1 is a potential biomarker for pan-cancer and promotes bladder cancer progression.Cancer medicine · 2024Article
- Article
- Integrated Bioinformatics and Experimental Analysis Identified TRIM28 a Potential Prognostic Biomarker and Correlated with Immune Infiltrates in Liver Hepatocellular Carcinoma.Computational and mathematical methods in medicine · 2022Article
- Identification of hub genes for early detection of bone metastasis in breast cancer.Frontiers in endocrinology · 2022Article
- Mechanisms of Xiaochaihu Decoction on Treating Hepatic Fibrosis Explored by Network Pharmacology.Disease markers · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Liver hepatocellular carcinoma (LIHC) has had a continuous increase in incidence and mortality rates over the last 40 years. Dynein Cytoplasmic 1 Heavy Chain 1 (DYNC1H1) is a protein coding gene which encodes the cytoplasmic dynein heavy chain family. This is the first investigation into the expression of DYNC1H1 and its mechanisms of action in LIHC patients. Methods: Based on the DYNC1H1 expression data from the TCGA database, we performed the DYNC1H1 expression, clinicopathological data, gene enrichment, and immune infiltration analysis. TIMER and CIBERSORT were used to assess immune responses of DYNC1H1 in LIHC. GEPIA, K-M survival analysis, and immunohistochemical staining pictures from the THPA were used to validate the results. In order to evaluate the diagnostic value of DYNC1H1, GEO datasets were analyzed by using ROC analysis. And quantitative real-time polymerase chain reaction was also carried out to evaluate the expression of DYNC1H1. Results: DYNC1H1 expression levels were associated with T classification, pathologic stage, histologic grade, and serum AFP levels. DYNC1H1 is an independent factor for a poor prognosis in patients with LIHC. Further study showed that high expression of DYNC1H1 was enriched in epithelial-mesenchymal transition (EMT) and the TGF Conclusions: DYNC1H1 will provide a novel and important perspective for the mechanisms of LIHC by regulating EMT. This gene will be able to act as an efficacious tool for the early diagnosis and effective intervention of LIHC.
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